Transformations in machining. Part 1. enhancement of wavelet transformation neural network (WT-NN) combination with a preprocessor

Properly selected transformation methods obtain the most significant characteristics of metal cutting data efficiently and simplify the classification. Wavelet Transformation (WT) and Neural Networks (NN) combination was used to classify the experimental cutting force data of milling operations previously. Preprocessing (PreP) of the approximation coefficients of the WT is proposed just before the classification by using the Adaptive Resonance Theory (ART2) type NNs. Genetic Algorithm (GA) was used to estimate the weights of each coefficient of the PreP. The WT-PreP-NN (ART2) combination worked at lower vigilances by creating only a few meaningful categories without any errors. The WT-NN (ART2) combination could obtain the same error rate only if very high vigilances are used and many categories are allowed.     

Thermodynamic state of reinforced interpenetrating polymer networks

The free energies of mixing of two networks in the interpenetrating polymer network based on crosslinked polyurethane and poly(ester acrylate) have been determined by the vapour sorption method. It was established that the constituent networks in the IPN are not miscible. The introduction of fillers of different chemical nature increases the compatibility. The thermodynamic affinity of the fillers to the individual networks and IPN was estimated. It was established that when the free energy of interaction of one or both components of the IPN with the filler is negative, reinforcement leads to the formation of a compatible and equilibrium system. For fillers having no affinity to the polymers, compatibilization is observed, which is connected with slowing down of phase separation in the system in the presence of filler.     

Memory of Distributed Computer Systems: Distinctive Features of Their Architectural-Structural Organization and Use

Distinctive features of architectural-structural organization and use of memory networks are considered with the aim of choosing an optimal configuration in designing distributed computer systems.     

永州电力通信交换网集中操作和维护的实现

分析实现永州电力通信交换网集中操作和维护的必要性，介绍了实现程控交换机远程操作和维护的两种方式，总结在实践过程中所得到的经验和教训。     

广播电视发射台技术指标集中自动测试系统

本文介绍了利用计算机技术、网络技术、三遥技术对广播电视发射技术指标进行实时自动测试的系统，以便进一步为安全优质播出提供技术保证。     

Artificial Neural Network Modeling of Osmotic Dehydration Mass Transfer Kinetics of Fruits

Artificial neural network (ANN) models were developed for the prediction of transient moisture loss (ML) and solid gain (SG) in osmotic dehydration of fruits using process kinetics data from the literature. ANN models for ML and SG were developed based on data over a broad range of operating conditions and ten common processing variables: temperature and concentration of osmotic solution, immersion time, initial water and solid content of the fruit, porosity, surface area, characteristic length, solution-to-fruit mass ratio, and agitation level. The trained models were able to accurately predict the outputs with associated regression coefficients (r) of 0.96 and 0.93, respectively, for ML and SG. These ANN models performed much better than those obtained from linear multivariate regression analysis. The large number of process variables and their wide ranges considered along with their easy implementation in a spreadsheet make them very useful and practical for process design and control.     

Study on phase behavior–impact strength relationship of unsaturated polyester/polyurethane hybrid polymer network

The phase behavior of a hybrid polymer network (HPN) composed of poly[(propylene glycol maleate)-co-(propylene glycol phthalate)] crosslinked with styrene and polyester–urethane crosslinked with methylene-bis-ortho-chloroaniline was examined. The correlation between phase separation and impact strength of the HPNs is discussed. The composition of HPNs has an effect on their properties.     

人工神经网络A／D变换器

本文对［５］的４位人工神经网络Ａ／Ｄ变换器进行了研究．指出按其方法推广实现多位Ａ／Ｄ时存在突触电阻大小以至无法实现且抗干扰能力也不好的问题并给出了解决办法．同时对如何改善神经元转移特性的硬限幅曲线作了简单讨论．     

Analysis of polarization plane rotation characteristic in 2D photonic crystal waveguide with chiral medium by condensed node spatial network

Using the photonic band gap in photonic crystals, the fundamental waveguide structures for the light wavelength range have been developed. Based on the fine structure of these many functional devices have been proposed by analytical or numerical simulation methods and the experiments of trial manufacture. In this paper, the treatment of chiral dielectric in the Condensed Node Spatial Network for the vector potential is explained, and we show the polarization plane rotation property in air‐hole and pillar type photonic crystal waveguide structures with the chiral medium substrate. Then, we show the fundamental advantage of the air‐hole type photonic crystal waveguide structure in application to a mode converter. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 152(1): 7–14, 2005; Published online in Wiley InterScience ( www.interscience. wiley.com ). DOI 10.1002/eej.20098     

浅谈下一代网络（NGN）

计算机网络的发展日新月异。下一代计算机网络（NGN）的探讨、研究已经成为当前的潮流。下一代网络是目前电信、互联网运营商和设备厂商都在讨论的热点技术，国内外许多网络运营商都在探讨，并正在或考虑建设试验网进行更深入的研究。本文介绍了NGN的定义、主要特点、分层结构和关键技术。